"... The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques ..."

The primary goal of patternrecognition is supervised or unsupervised classification. Among the various frameworks in which patternrecognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network

"... Abstract – A method for applying pattern recognition techniques to recognize the identity of a person based on their iris is proposed. Hidden Markov Models are used to parametrically model the local frequencies of the iris. Also discussed is a transform of the iris image from two to one dimensional ..."

Abstract – A method for applying patternrecognition techniques to recognize the identity of a person based on their iris is proposed. Hidden Markov Models are used to parametrically model the local frequencies of the iris. Also discussed is a transform of the iris image from two to one dimensional

by
David M. Magerman
- Proc. of the 33rd Annual Meeting of the ACL, 1995

"... this paper represents a movement away from traditional grammar-based parsing towards parsing as pattern recognition, where the pattern to be recognized is a linguistic analysis of a sentence. This approach divides the parsing problem into two separate tasks: treebanking, defining the annotation sche ..."

this paper represents a movement away from traditional grammar-based parsing towards parsing as patternrecognition, where the pattern to be recognized is a linguistic analysis of a sentence. This approach divides the parsing problem into two separate tasks: treebanking, defining the annotation

"... This paper discusses a geometry associated with U-divergence including ideas of U-models, U-loss functions of two versions. On the basis of the geometry we observe that U-divergence projection of a data distribution p onto U-model MU associates with the Pythagorean relation for the triangle connecti ..."

connection of p q and q∗, for any q of the U-model where q ∗ denotes the point of MU projected from p. This geometric consideration is implemented on the problem of sta-tisticalpatternrecognition. U-Boost algorithm proposed in the practical application is shown to pursue iteratively the U

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Visit our Home Page on www.wileyeurope.com or www.wiley.com All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of

"... We integrate the tangent method into a statistical framework for classification analytically and practically. The resulting consistent framework for adaptation allows us to efficiently estimate the tangent vectors representing the variability. The framework improves classification results on two ..."

by
Teuvo Kohonen, Gyorgy Barna, Ronald Chrisley
- Proceedings of the Second Annual IEEE International Conference on Neural Networks, 1988

"... Successful recognition of natural signals, e.g., speech recognition, requires substantial statistical pattern recognition capabilities. This is at odds with the fact that the bulk of work on applying neural networks to pattern recognition has concentrated on non-statistical problems. Three basic typ ..."

Successful recognition of natural signals, e.g., speech recognition, requires substantial statisticalpatternrecognition capabilities. This is at odds with the fact that the bulk of work on applying neural networks to patternrecognition has concentrated on non-statistical problems. Three basic